We compared our method to two different L1-wavelet [1]} reconstructions, implemented using BART [2]}, where (1) uses motion corrupt data and (2) uses motion free data. For prior methods which rely on SENSE based schemes [3]} for the final reconstruction [4]}, [5]}, [6]} (1) represents the worst case scenario while (2) represents the best case scenario. Our method, however, jointly estimated motion parameters and the image. We performed experiments on 11 validation slices and 39 test slices from the T2-weighted brain fastMRI dataset at retrospective acceleration factors of (\(R=4,4.8,6\) ). Each slice was independently corrupted by motion and additive Gaussian noise.
